Causal Decision Agent

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rdbalance

Read-only

Tests whether covariates are balanced at the RD cutoff to validate the regression discontinuity design's key assumption.

Instructions

Covariate balance test at the RD cutoff.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`c`	No	Cutoff.
`h`	No	Manual bandwidth. If None, uses MSE-optimal per covariate.
`p`	No	p parameter (int).
`x`	Yes	Running variable name.
`covs`	No	Covariate names to test. If None, tests all numeric columns except x.
`alpha`	No	Significance level for confidence intervals and tests.
`detail`	No	Payload depth: 'minimal' (~150 tokens) for sub-step calls where only the point estimate is needed; 'standard' (~1K tokens) for diagnostics + coefficient table; 'agent' (~2K tokens, default) adds violations / next_steps / suggested_functions so the LLM can plan its next call without another round-trip.	agent
`kernel`	No	Kernel function used for weighting or smoothing.	triangular
`as_handle`	No	If true, cache the fitted result on the server and return result_id + result_uri alongside the JSON payload so a subsequent tools/call can chain without re-running.
`data_path`	Yes	Absolute path or URL to a data file. Supported: .csv / .tsv / .txt (delimited), .parquet / .pq, .feather / .arrow, .xlsx / .xls, .dta (Stata), .json / .jsonl. Schemes: file://, s3://, gs://, https://.
`result_id`	No	Optional handle to a previously-fitted result (returned by an earlier call when as_handle=true). Tools that operate on a fitted object accept this in place of re-supplying data_path + columns.
`data_columns`	No	Optional column projection. Parquet/Feather/Stata loaders honour this for fast partial reads.
`data_sample_n`	No	Optional uniform random subsample size (seed=0, deterministic) — useful on huge panels.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 15, 2026

TDQS

B3.3/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds no behavioral disclosure beyond what the annotations already provide: readOnlyHint=true and openWorldHint=false. It does not describe method details, output behavior, or caveats, and it does not contradict the annotations, but it also contributes no independent behavioral transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler or redundant wording. Every word contributes to identifying the tool's core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The output schema and detailed parameter descriptions cover much of the operational surface, and the annotations safely mark it read-only. However, the free-text description alone is thin for selecting among the many closely related RD tools in the sibling list, and it never explains how this test relates to rdwinselect, rddensity, or rdsummary.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema already documents all 13 parameters. The description adds only the phrase 'covariate balance,' which hints at the covs parameter, but it does not add operational meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: it performs a covariate balance test at the RD cutoff. This distinguishes it from estimation, density, and plotting RD siblings such as rdrobust, rddensity, and rdplot. However, it does not explicitly contrast itself with close relatives like rdwinselect, so it stops just short of full differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'covariate balance test at the RD cutoff' implies the diagnostic context in which the tool should be used. Yet the description gives no explicit when-to-use guidance, no exclusions, and no mention of alternatives for related RD tasks such as bandwidth selection or density testing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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